The ability to quickly and intelligently interpret large data sets is a basic asset in the modern computing environment. To that end, various modern databases provide optimized structures that enable and accommodate quick and efficient searching. In an effort to reduce latency, it has been suggested that databases, or portions thereof, may be stored in dynamic random-access memory (DRAM) rather than in storage media such as hard drives or SSD flash drives, as DRAM has a much lower latency than many other common types of storage media. This approach can, indeed, increase the performance of a database; however, a nontrivial amount of power is typically required to drive data off of the DRAM to a processor, e.g., for comparison during the execution of a search query. Thus, there is a need for new memory architectures and methods to improve upon the current state of the art.